[1] [1] Ji Z J. The research of APD single photon counting imaging experiment［D］. Nanjing:Nanjing University of Science and Technology, 2012: 4-7.

[2] [2] Chang C. Noise characteristic of AlGaN avalanche photodiodes measurement and analysis［D］. Shanghai: Graduate School of Chinese Academy of Sciences (Shanghai Institute of Technical Physics), 2015: 22-25.

[3] [3] Wang F. Research on the measurement and application of avalanche photodiodes noise［D］. Xi′an: Xidian University, 2011: 39-47.

[4] [4] Liu J Y. Research on contour grouping for low-light images［D］. Beijing: Beijing Jiaotong University, 2010: 18-26.

[5] [5] Wu W, Peng H, Zhou Z K. Improved FastICA algorithm and its application in noisy blind sources separation［J］. Journal of Information Engineering University, 2013, 14(6): 708-712.

[6] [6] Meng Z, Ma Z, Liu D, et al. Blind source separation based on wavelet semi-soft threshold denoising［J］. China Mechanical Engineering, 2016, 27(3): 337-342.

[7] [7] Cai W H,He X S. Noisy blind source separation based on undecimated wavelet transform and independent component analysis［J］. Computer Engineering and Applications, 2016, 52(16): 180-185.

[8] [8] Zhao K, Huang G M. FastICA blind source separation based on secondary-wavelet denoising［J］. Ship Electronic Engineering, 2015, 35(6): 36-40.

[9] [9] Wang X. The study on blind separation of noisy speech mixtures［D］. Beijing: Beijing Jiaotong University, 2014: 20-27.

[10] [10] Jia W K, Zhao D A, Ruan C Z, et al. Combined method for night vision image denoising based on wavelet transform and ICA［J］. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(9): 9-17.

[11] [11] Wu W. Research on noisy blind source separation algorithm and its application in underwater acoustic signals［D］. Zhengzhou: PLA Information Engineering University, 2014: 104-110.

[12] [12] Li J, Cheng C K, Jiang T Y, et al. Wavelet de-noising of partial discharge signals based on genetic adaptive threshold estimation［J］. IEEE Transactions on Dielectrics and Electrical Insulation, 2012, 19(2): 543-549.

[13] [13] Jiang H, Su Y. Denoising method based on improved wavelet threshold function［J］. Laser & Infrared, 2016, 46(1): 119-122.

[14] [14] Donoho D L, Johnstone J M. Ideal spatial adaptation by wavelet shrinkage［J］. Biometrika, 1994, 81(3): 425-455.

[15] [15] Chang S G, Yu B, Vetterli M. Adaptive wavelet thresholding for image denoising and compression［J］. IEEE Transactions on Image Processing, 2000, 9(9): 1532-1546.

[16] [16] Li D M, Gai M Y, Li C R, et al. Research on adaptive optics image denoising algorithm based on the wavelet-based contourlet transform［J］. Laser & Optoelectronics Progress, 2015, 52(11): 111001.

[17] [17] Guo W, Wang R S, Zhang P, et al. Image denoising based independent component analysis［J］.Signal Processing, 2008, 24(3): 381-385.

[18] [18] Zhao C B. Research of image denoising based on blind source separation［J］. Harbin: Harbin Engineering University, 2015: 49-61.

[19] [19] Oja E, Yuan Z J. The FastICA algorithm revisited: convergence analysis［J］. IEEE Transactions on Neural Networks, 2006, 17(6): 1370-1381.

[20] [20] Novey M, Adali T. On extending the complex FastICA algorithm to noncircular sources［J］. IEEE Transactions on Signal Processing, 2008, 56(5): 2148-2154.